Using Genetic Algorithm in the Multiprocessor Flow Shop to Minimize the Makespan

Besbes, Walid; Loukil, Taïcir; Teghem, Jacques

doi:10.1109/icsssm.2006.320684

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…In this context, a mathematical program is proposed for the FSH problem with availability constraints while implicitly using a B&B. In [8] a mathematical model is presented for the 2FHD|s j , m j |C max that was implemented with Clpex and was only able to solve small instances (25 jobs). In [9], the authors give a mixed programming formulation (MILP) and three heuristics for the m machine flow problem with the objective of minimizing the makespan and maximizing the total net revenue.…”

Section: Literature Reviewmentioning

confidence: 99%

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Makespan Minimization for the Two-Stage Hybrid Flow Shop Problem with Dedicated Machines: A Comprehensive Study of Exact and Heuristic Approaches

2023

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This paper presents a comprehensive approach for minimizing makespan in the challenging two-stage hybrid flowshop with dedicated machines, a problem known to be strongly NP-hard. This study proposed a constraint programming approach, a novel heuristic based on a priority rule, and Tabu search procedures to tackle this optimization problem. The constraint programming model, implemented using a commercial solver, serves as the exact resolution method, while the heuristic and Tabu search explore approximate solutions simultaneously. The motivation behind this research is the need to address the complexities of scheduling problems in the context of two-stage hybrid flowshop with dedicated machines. This problem presents significant challenges due to its NP-hard nature and the need for efficient optimization techniques. The contribution of this study lies in the development of an integrated approach that combines constraint programming, a novel heuristic, and Tabu search to provide a comprehensive and efficient solution. The proposed constraint programming model offers exact resolution capabilities, while the heuristic and Tabu search provide approximate solutions, offering a balance between accuracy and efficiency. To enhance the search process, the research introduces effective elimination rules, which reduce the search space and simplify the search effort. This approach improves the overall optimization performance and contributes to finding high-quality solutions. The results demonstrate the effectiveness of the proposed approach. The heuristic approach achieves complete success in solving all instances for specific classes, showcasing its practical applicability. Furthermore, the constraint programming model exhibits exceptional efficiency, successfully solving problems with up to n=500 jobs. This efficiency is noteworthy compared to instances solved by other exact solution approaches, indicating the scalability and effectiveness of the proposed method.

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Section: Literature Reviewmentioning

confidence: 99%

“…The constraint (7) indicates that a job can only start its execution on the second stage once its operation on the first stage is finished. The constraint (8) defines the makespan to be minimized.…”

Section: Csp Model Variablesmentioning

confidence: 99%

Makespan Minimization for the Two-Stage Hybrid Flow Shop Problem with Dedicated Machines: A Comprehensive Study of Exact and Heuristic Approaches

2023

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“…Santos et al (1996) adapted some pure flow-shop heuristics in the HFS environment. Various intelligent heuristics and meta-heuristics have become popular such as simulated annealing (SA) (Gourgand, Grangeon, & Norre, 1999;Jin, Yang, & Ito, 2006), tabu search (TS) (Nowicki & Smutnicki, 1998), genetic algorithms (GA) (Portmann, Vignier, Dardilhac, & Dezalay, 1998;Jin, Ohno, Ito, & Elmaghraby, 2002;Besbes, Loukil, & Teghem, 2006), approaches based on artificial immune systems (AIS) (Engin & Döyen, 2004).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The different results obtained by our approach is presented and compared with a B&B procedure (Néron et al, 2001), two ACO algorithms (HACS-HFS) (Khalouli, Ghedjati, & Hamzaoui, 2008) and Improved-AS (Alaykýran, Engin, & Döyen, 2007), a GA (Besbes, Loukil, Teghem, 2006) and an AIS (Engin & Döyen, 2004). According to Table 2 and Table 3, better results have been obtained for a and b type problems than c and d type problems.…”

Section: Computational Experimentsmentioning

confidence: 99%

An Ant Colony System Algorithm for the Hybrid Flow-Shop Scheduling Problem

Khalouli

Ghedjati

Hamzaoui

2011

International Journal of Applied Metaheuristic Computing

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An integrated ant colony optimization algorithm (IACS-HFS) is proposed for a multistage hybrid flow-shop scheduling problem. The objective of scheduling is the minimization of the makespan. To solve this NP-hard problem, the IACS-HFS considers the assignment and sequencing sub-problems simultaneously in the construction procedures. The performance of the algorithm is evaluated by numerical experiments on benchmark problems taken from the literature. The results show that the proposed ant colony optimization algorithm gives promising and good results and outperforms some current approaches in the quality of schedules.

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Taking advantage of a diverse set of efficient production schedules: A two-step approach for scheduling with side concerns

Goren

Pierreval

2013

Computers & Operations Research

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Using Genetic Algorithm in the Multiprocessor Flow Shop to Minimize the Makespan

Cited by 6 publications

References 12 publications

Makespan Minimization for the Two-Stage Hybrid Flow Shop Problem with Dedicated Machines: A Comprehensive Study of Exact and Heuristic Approaches

Makespan Minimization for the Two-Stage Hybrid Flow Shop Problem with Dedicated Machines: A Comprehensive Study of Exact and Heuristic Approaches

An Ant Colony System Algorithm for the Hybrid Flow-Shop Scheduling Problem

Taking advantage of a diverse set of efficient production schedules: A two-step approach for scheduling with side concerns

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